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Found 12 papers, 11 papers with code
Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model
In contrast, the newly proposed Mamba model, based on state space models (SSM), outperforms Transformer in multiple areas with only linear complexity.
Ranked #3 on
3D Point Cloud Classification
on ModelNet40
(using extra training data)
PDF: A Probability-Driven Framework for Open World 3D Point Cloud Semantic Segmentation
Existing point cloud semantic segmentation networks cannot identify unknown classes and update their knowledge, due to a closed-set and static perspective of the real world, which would induce the intelligent agent to make bad decisions.
Couler: Unified Machine Learning Workflow Optimization in Cloud
This variety poses a challenge for end-users in terms of mastering different engine APIs.
Point-LGMask: Local and Global Contexts Embedding for Point Cloud Pre-training with Multi-Ratio Masking
In our work, we present Point-LGMask, a novel method to embed both local and global contexts with multi-ratio masking, which is quite effective for self-supervised feature learning of point clouds but is unfortunately ignored by existing pre-training works.
Ranked #3 on
Few-Shot 3D Point Cloud Classification
on ModelNet40 5-way (10-shot)
(using extra training data)
CasFusionNet: A Cascaded Network for Point Cloud Semantic Scene Completion by Dense Feature Fusion
In our work, we present CasFusionNet, a novel cascaded network for point cloud semantic scene completion by dense feature fusion.
A Scalable and Cloud-Native Hyperparameter Tuning System
In this paper, we introduce Katib: a scalable, cloud-native, and production-ready hyperparameter tuning system that is agnostic of the underlying machine learning framework.
SQLFlow: A Bridge between SQL and Machine Learning
Previous database systems extended their SQL dialect to support ML.
metric-learn: Metric Learning Algorithms in Python
metric-learn is an open source Python package implementing supervised and weakly-supervised distance metric learning algorithms.
Autoplotly - Automatic Generation of Interactive Visualizations for Popular Statistical Results
The autoplotly package provides functionalities to automatically generate interactive visualizations for many popular statistical results supported by ggfortify package with plotly and ggplot2 style.
Computation Applications
TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks
Our focus is on simplifying cutting edge machine learning for practitioners in order to bring such technologies into production.
TF.Learn: TensorFlow's High-level Module for Distributed Machine Learning
TF. Learn is a high-level Python module for distributed machine learning inside TensorFlow.
BIG-bench Machine Learning
Vocal Bursts Intensity Prediction
lfda: An R Package for Local Fisher Discriminant Analysis and Visualization
Local Fisher discriminant analysis is a localized variant of Fisher discriminant analysis and it is popular for supervised dimensionality reduction method.
Applications
